Christa Neuper

Motor imagery activates primary sensorimotor area in humans

The spatiotemporal patterns of Rolandic mu and beta rhythms were studied during motor imagery with a dense array of EEG electrodes. The subjects were instructed to imagine movements of either the right or the left hand, corresponding to visual stimuli on a computer screen. It was found that unilateral motor imagery results in a short-lasting and localized EEG change over the primary sensorimotor area. The Rolandic rhythms displayed an event-related desynchronization (ERD) only over the contralateral hemisphere. In two of the three investigated subjects, an enhanced Rolandic rhythm was found over the ipsilateral side. The pattern of EEG desynchronization related to imagination of a movement was similar to the pattern during planning of a voluntary movement.

Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters

Electroencephalogram (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by, e.g., patients with amyotrophic lateral sclerosis (ALS) to develop a simple binary response in order to reply to specific questions. Four subjects participated in a series of on-line sessions with an EEG-based cursor control. The EEG was recorded from electrodes overlying sensory-motor areas during left and right motor imagery. The EEG signals were analyzed in subject-specific frequency bands and classified on-line by a neural network. The network output was used as a feedback signal. The on-line error (100%-perfect classification) was between 10.0 and 38.1%. In addition, the single-trial data were also analyzed off-line by using an adaptive autoregressive (AAR) model of order 6. With a linear discriminant analysis the estimated parameters for left and right motor imagery were separated. The error rate obtained varied between 5.8 and 32.8% and was, on average, better than the on-line results. By using the AAR-model for on-line classification an improvement in the error rate can be expected, however, with a classification delay around 1 s.

ERD/ERS patterns reflecting sensorimotor activation and deactivation.

Oscillations in the alpha and beta band (<35 Hz) show characteristic spatiotemporal patterns during sensorimotor processing. Whereas event-related desynchronization (ERD) during motor preparation, execution, and imagery can be seen as a correlate of an activated cortical area, event-related synchronization (ERS) of frequency components between 10 and 13 Hz may represent a deactivated cortical area or inhibited cortical network, at least under certain conditions. Induced beta rhythms (13-35 Hz, beta ERS) can be found in sensorimotor areas following both voluntary movement and somatosensory stimulation. In a recent study we used different tasks involving execution and imagery of movements of the upper and lower limb to produce activation vs. deactivation/inhibition of the sensorimotor hand area. Sensorimotor interference, as a function of the activation level of the motor cortex, was studied by the use of repetitive median nerve stimulation (MNS) (ISI 1.5 s) in 12 healthy volunteers during the following task conditions: (i) cube manipulation between thumb and fingers of one hand, (ii) imagined cube manipulation, (iii) continuous foot rotation movements, and (iv) imagined foot movements. EEG was recorded from hand and foot representation areas and processed time-locked to MNS (ERD/ERS). In addition, task-related band power changes (TRPD/TRPI) were analyzed. We found a clear-cut suppression of the stimulation-induced beta ERS (indicating an enhanced activity state of the sensorimotor areas) during active cube manipulation and a weaker suppression during cube imagery. Mental imagination of foot movement led to an increase of the hand area mu rhythm, but did not interfere with stimulation-related effects on beta ERS. These findings support that interfering sensorimotor activation and deactivation is reflected in graduated changes of induced mu and beta oscillations.

Information transfer rate in a five-classes brain-computer interface

The information transfer rate, given in bits per trial, is used as an evaluation measurement in a brain-computer interface (BCI). Three subjects performed four motor-imagery (left hand, right hand, foot, and tongue) and one mental-calculation task. Classification of the EEG patterns is based on band power estimates and hidden Markov models. We propose a method that combines the EEG patterns based on separability into subsets of two, three, four, and five mental tasks. The information transfer rates of the BCI systems comprised of these subsets are reported. The achieved information transfer rates vary from 0.42 to 0.81 bits per trial and reveal that the upper limit of different mental tasks for a BCI system is three. In each subject, different combinations of three tasks resulted in the best performance.

Rapid prototyping of an EEG-based brain-computer interface (BCI)

The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional DSP board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive model and linear discriminant analysis.

To retrieve or to calculate? Left angular gyrus mediates the retrieval of arithmetic facts during problem solving.

While there is consistent evidence from neuropsychological and brain imaging studies for an association between the left angular gyrus and mental arithmetic, its specific role in calculation has remained poorly understood. It has been speculated that the angular gyrus mediates the retrieval of arithmetic facts during problem solving, but this hypothesis has not been directly tested. In the present functional Magnetic Resonance Imaging study comprising 28 adults, we used trial-by-trial strategy self-reports to identify brain regions underpinning different strategies in arithmetic problem solving. Analyses revealed stronger activation of the left angular gyrus while solving arithmetic problems for which participants reported fact retrieval whereas the application of procedural strategies was accompanied by widespread activation in a fronto-parietal network. These data directly link the left angular gyrus with arithmetic fact retrieval and show that strategy self-reports can be used to predict differential patterns of brain activation.

The creative brain: Investigation of brain activity during creative problem solving by means of EEG and FMRI

Cortical activity in the EEG alpha band has proven to be particularly sensitive to creativity‐related demands, but its functional meaning in the context of creative cognition has not been clarified yet. Specifically, increases in alpha activity (i.e., alpha synchronisation) in response to creative thinking can be interpreted in different ways: As a functional correlate of cortical idling, as a sign of internal top‐down activity or, more specifically, as selective inhibition of brain regions. We measured brain activity during creative thinking in two studies employing different neurophysiological measurement methods (EEG and fMRI). In both studies, participants worked on four verbal tasks differentially drawing on creative idea generation. The EEG study revealed that the generation of original ideas was associated with alpha synchronisation in frontal brain regions and with a diffuse and widespread pattern of alpha synchronisation over parietal cortical regions. The fMRI study revealed that task performance was associated with strong activation in frontal regions of the left hemisphere. In addition, we found task‐specific effects in parietotemporal brain areas. The findings suggest that EEG alpha band synchronisation during creative thinking can be interpreted as a sign of active cognitive processes rather than cortical idling. Hum Brain Mapp, 2009.

Individual differences in mathematical competence predict parietal brain activation during mental calculation

Functional neuroimaging studies have revealed that parietal brain circuits subserve arithmetic problem solving and that their recruitment dynamically changes as a function of training and development. The present study investigated whether the brain activation during mental calculation is also modulated by individual differences in mathematical competence. Twenty-five adult students were selected from a larger pool based on their performance on standardized tests of intelligence and arithmetic and divided into groups of individuals with relatively lower and higher mathematical competence. These groups did not differ in their non-numerical intelligence or age. In an fMRI block-design, participants had to verify the correctness of single-digit and multi-digit multiplication problems. Analyses revealed that the individuals with higher mathematical competence displayed stronger activation of the left angular gyrus while solving both types of arithmetic problems. Additional correlational analyses corroborated the association between individual differences in mathematical competence and angular gyrus activation, even when variability in task performance was controlled for. These findings demonstrate that the recruitment of the left angular gyrus during arithmetic problem solving underlies individual differences in mathematical ability and suggests a stronger reliance on automatic, language-mediated processes in more competent individuals.

Simultaneous Eeg 10 Hz desynchronization and 40 Hz synchronization during finger movements

Nineteen-channel EEG was recorded with closely spaced electrodes overlaying the left sensorimotor cortex during self-paced, voluntary right finger movements. Three right-handed people served as subjects. The EEG was analysed in the 10 Hz band (10-12 Hz) and in four 40 Hz bands (34-36, 36-38, 38-40, 40-42) by calculation of ERD time courses and ERD maps, whereby a ERD is characterized by a movement-related band power decrease. In all three subjects a close to C3 localized 10 Hz ERD was found, starting about 2 s prior to movement onset and continuing during movement. Along with this 10 Hz ERD a localized and short-lasting (about 0.5 s) burst of 40 Hz oscillations was embedded around movement onset. This can be interpreted as indicating that planning of movement is accompanied by a desynchronization of central mu rhythm and a generation of 40 Hz oscillations.

Enhancement of left-right sensorimotor EEG differences during feedback-regulated motor imagery.

EEG feedback studies demonstrate that human subjects can learn to regulate electrocortical activity over the sensorimotor cortex. Such self-induced EEG changes could serve as control signals for a Brain Computer Interface. The experimental task of the current study was to imagine either right-hand or left-hand movement depending on a visual cue stimulus on a computer monitor. The performance of this imagination task was controlled on-line by means of a feedback bar that represented the current EEG pattern. EEG signals recorded from left and right central recording sites were used for on-line classification. For the estimation of EEG parameters, an adaptive autoregressive model was applied, and a linear discriminant classifier was used to discriminate between EEG patterns associated with left and right motor imagery. Four trained subjects reached 85% to 95% classification accuracy in the course of the experimental sessions. To investigate the impact of continuous feedback presentation, time courses of band power changes were computed for subject-specific frequency bands. The EEG data revealed a significant event-related desynchronization over the contralateral central area in all subjects. Two subjects simultaneously displayed synchronization of EEG activity (event-related synchronization) over the ipsilateral side. During feedback presentation the event-related desynchronization/event-related synchronization patterns showed increased hemispheric asymmetry compared to initial control sessions without feedback.